Statistical Methods in Medical Research 2010; 19: 3–4 Editorial

Recent developments in survival analysis Survival analysis is one of the oldest statistical disciplines with roots in the 17th and 18th century demography and actuarial science. Thus, both the life-table, the standardised mortality ratio and discussions of competing risks date back to that period (see e.g. Andersen and Keiding1 for a brief account). Later, in the 19th century, parametric (Gompertz-Makeham) models were used for studies of the distribution of human life times. In spite of this long history, survival analysis was not really an integrated part of theoretical statistics in the beginning of the 20th century as illustrated by the rather sceptical papers by Greenwood2 and Westergaard,3 and only in the mid-century were these well-established methods from demography and actuarial science presented to the medical-statistical community.4,5 The classical methods were based on time-grouped data but at this time a new kind of data were emerging in clinical research where smaller samples of patients were studied in clinical trials in chronic diseases. These trials typically produced exact event times